Peripheral T-cell lymphomas (PTCLs) represent a poorly understood group of aggressive hematologic malignancies. Only one-third of patients survive 5 years from the time of diagnosis. Most patients receive a chemotherapy regimen (CHOP) that originally was designed for other types of lymphoma and is suboptimal in PTCL. Following CHOP by stem-cell transplantation has shown promise, but carries increased toxicity. Newer chemotherapy drugs also have shown benefits in some patients. However, few biomarker tests currently are available to identify which therapy is most appropriate for a given patient. Genetic testing plays a key role in stratifying patients for individualized therapy in othr hematologic malignancies, but application of this approach to PTCL has been hindered because the genetics of PTCL are incompletely understood. Based on the urgent need for biomarkers to predict clinical behavior in PTCL, we formulated three fundamental questions that need to be answered: 1) What are the recurrent genetic abnormalities in PTCL? 2) Which genetic biomarkers best enhance current risk assessment tools? 3) Which genetic biomarkers predict chemosensitivity to drugs used to treat PTCL? Our research team has made major contributions to understanding the genetics of PTCL and thus is well equipped to address these questions in a highly innovative and comprehensive way. In Aim 1, we will use a bioinformatic approach to analyze a discovery set of 66 PTCL tumor samples on which we already have performed next generation sequencing and gene expression profiling. In Aim 2, we will combine our previous discoveries with findings by others and the highest priority candidates from Aim 1 to identify which combination of biomarkers is most helpful in identifying high- and low-risk patients in an independent validation set of 332 PTCLs. In Aim 3, we will determine how particular genetic abnormalities contribute to the sensitivity of PTCL cells to chemotherapeutic drugs. We believe these studies are highly likely to change the clinical management of PTCL patients. In the short term, we anticipate that improving risk assessment will lead to changes in selection of patients to receive standard vs. intensified vs. experimental therapy. In the longer term, we believe our results will allow individualized selection of chemotherapy drugs based on the pattern of genetic abnormalities in PTCL tumor tissue.